IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i12p3046-d370772.html
   My bibliography  Save this article

Bi-level Capacity Planning of Wind-PV-Battery Hybrid Generation System Considering Return on Investment

Author

Listed:
  • Bowen Yang

    (Department of Information Engineering, Xiangtan University, Xiangtan 411105, China)

  • Yougui Guo

    (Department of Information Engineering, Xiangtan University, Xiangtan 411105, China)

  • Xi Xiao

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Peigen Tian

    (Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

Abstract

Reasonable configuration of equipment capacity can effectively improve the economics of wind-photovoltaic-battery hybrid generation system (WPB-HGS). Based on the current needs of investors to pay more attention to the economic benefits of WPB-HGS, this paper proposes a capacity configuration method for WPB-HGS considering return on investment (ROI). A bi-level planning model for integrated planning and operation of WPB-HGS was established. The lower-level model optimizes the system’s operating status with the goal of maximizing the daily power sales of the system. The upper-level model plans the equipment capacity of the WPB-HGS with the goal of maximizing the annual net income and return on investment. The model is solved using adaptive weighted particle swarm optimization. According to actual engineering examples, the specific equipment capacity is configured, and the configuration results are analyzed to verify the effectiveness of the method.

Suggested Citation

  • Bowen Yang & Yougui Guo & Xi Xiao & Peigen Tian, 2020. "Bi-level Capacity Planning of Wind-PV-Battery Hybrid Generation System Considering Return on Investment," Energies, MDPI, vol. 13(12), pages 1-18, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3046-:d:370772
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/12/3046/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/12/3046/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mahmoud G. Hemeida & Salem Alkhalaf & Al-Attar A. Mohamed & Abdalla Ahmed Ibrahim & Tomonobu Senjyu, 2020. "Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO)," Energies, MDPI, vol. 13(15), pages 1-37, July.
    2. Olexandr Shavolkin & Juraj Gerlici & Iryna Shvedchykova & Kateryna Kravchenko, 2022. "Solar–Wind System for the Remote Objects of Railway Transport Infrastructure," Energies, MDPI, vol. 15(18), pages 1-19, September.
    3. Dahu Li & Xiaoda Cheng & Leijiao Ge & Wentao Huang & Jun He & Zhongwei He, 2022. "Multiple Power Supply Capacity Planning Research for New Power System Based on Situation Awareness," Energies, MDPI, vol. 15(9), pages 1-24, April.
    4. Olexandr Shavolkin & Iryna Shvedchykova & Michal Kolcun & Dušan Medved’, 2022. "Improvement of the Grid-Tied Solar-Wind System with a Storage Battery for the Self-Consumption of a Local Object," Energies, MDPI, vol. 15(14), pages 1-18, July.
    5. Ana Rita Silva & Ana Estanqueiro, 2022. "From Wind to Hybrid: A Contribution to the Optimal Design of Utility-Scale Hybrid Power Plants," Energies, MDPI, vol. 15(7), pages 1-19, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3046-:d:370772. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.